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Related Concept Videos

Protein Families02:47

Protein Families

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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Gene Evolution - Fast or Slow?02:05

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Related Experiment Video

Updated: Dec 24, 2025

Identification of Plant Ice-binding Proteins Through Assessment of Ice-recrystallization Inhibition and Isolation Using Ice-affinity Purification
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Identification of Plant Ice-binding Proteins Through Assessment of Ice-recrystallization Inhibition and Isolation Using Ice-affinity Purification

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Identifying Antifreeze Proteins Based on Key Evolutionary Information.

Shanwen Sun1, Hui Ding2, Donghua Wang3

  • 1Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China.

Frontiers in Bioengineering and Biotechnology
|April 11, 2020
PubMed
Summary
This summary is machine-generated.

Antifreeze proteins are vital for industry but limited in supply and can be toxic. This study identifies key evolutionary features to accurately classify antifreeze proteins, aiding industrial applications.

Keywords:
antifreeze proteinsevolutionmachine learningposition-specific scoring matrixsupport vector machine

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Determining the Ice-binding Planes of Antifreeze Proteins by Fluorescence-based Ice Plane Affinity
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Area of Science:

  • Biochemistry and Molecular Biology
  • Bioinformatics
  • Materials Science

Background:

  • Antifreeze proteins (AFPs) are crucial for industrial applications like cryopreservation and food storage.
  • Current limitations include insufficient production quantities and cytotoxicity, hindering widespread use.
  • Understanding AFP-ice interactions and identifying novel AFPs are critical for advancing these applications.

Purpose of the Study:

  • To elucidate the mechanisms of protein-ice interactions.
  • To develop an efficient and accurate computational tool for identifying antifreeze proteins.
  • To leverage evolutionary information for AFP discrimination.

Main Methods:

  • Analysis of evolutionary features using position-specific scoring matrices (PSSMs).
  • Selection of seven key features with high discriminatory importance.
  • Application of principal component analysis (PCA) to evaluate feature contributions.
  • Development of a support vector machine (SVM) classifier based on selected features.

Main Results:

  • Identified seven key evolutionary features distinguishing antifreeze from non-antifreeze proteins.
  • Observed opposite amino acid conservation tendencies between antifreeze and non-antifreeze proteins.
  • PCA revealed significant contributions from specific amino acid replacements (e.g., Cys, Trp, Gly, Arg) to discrimination.
  • The developed SVM classifier outperformed existing state-of-the-art tools.

Conclusions:

  • Evolutionary information is essential for accurate automated discrimination of antifreeze proteins.
  • The developed classifier provides an efficient method for annotating new proteins with antifreeze functions.
  • This tool can accelerate the industrial application of novel antifreeze proteins.